Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Editorial
. 2023 Mar;39(2):109-111.
doi: 10.1007/s12055-023-01478-8. Epub 2023 Jan 26.

Predicting the unpredictable in cardiothoracic surgery

Affiliations
Editorial

Predicting the unpredictable in cardiothoracic surgery

Om Prakash Yadava. Indian J Thorac Cardiovasc Surg. 2023 Mar.
No abstract available

PubMed Disclaimer

Conflict of interest statement

Conflict of interestNil.

Similar articles

References

    1. Sabrina S, Daan N, Yvonne V, et al. Improved prediction by dynamic modeling. An exploratory study in the adult cardiac surgery database of the Netherlands Association for Cardio-Thoracic Surgery. Circ Cardiovasc Qual Outcomes. 2016;9:171–181. doi: 10.1161/CIRCOUTCOMES.114.001645. - DOI - PubMed
    1. Sherman E, Alejo D, Wood-Doughty Z, et al. Leveraging machine learning to predict 30-day hospital readmission after cardiac surgery. Ann Thorac Surg. 2022;114:2173–9. doi: 10.1016/j.athoracsur.2021.11.011. - DOI - PubMed
    1. Park J, Bonde PN. Machine learning in cardiac surgery: predicting mortality and readmission. ASAIO J. 2022;68:1490–1500. doi: 10.1097/MAT.0000000000001696. - DOI - PubMed
    1. Orfanoudaki A, Giannoutsou A, Hashim S, Bertsimas D, Hagberg RC. Machine learning models for mitral valve replacement: a comparative analysis with the Society of Thoracic Surgeons risk score. J Card Surg. 2022;37:18–28. doi: 10.1111/jocs.16072. - DOI - PubMed
    1. Kilic A, Habib RH, Miller JK, Shahian DM, Dearani JA, Dubrawski AW. Supplementing existing societal risk models for surgical aortic valve replacement with machine learning for improved prediction. J Am Heart Assoc. 2021;10:e019697. doi: 10.1161/JAHA.120.019697. - DOI - PMC - PubMed

Publication types

LinkOut - more resources